949 resultados para heat demand
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Recent changes in power systems mainly due to the substantial increase of distributed generation and to the operation in competitive environments has created new challenges to operation and planning. In this context, Virtual Power Players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Demand response market implementation has been done in recent years. Several implementation models have been considered. An important characteristic of a demand response program is the trigger criterion. A program for which the event trigger depends on the Locational Marginal Price (LMP) used by the New England Independent System operator (ISO-NE) inspired the present paper. This paper proposes a methodology to support VPP demand response programs management. The proposed method has been computationally implemented and its application is illustrated using a 32 bus network with intensive use of distributed generation. Results concerning the evaluation of the impact of using demand response events are also presented.
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The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.
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In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.
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In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer’s profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer’s profit. The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers’ decision making.
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Power systems are planed and operated according to the optimization of the available resources. Traditionally these tasks were mostly undertaken in a centralized way which is no longer adequate in a competitive environment. Demand response can play a very relevant role in this context but adequate tools to negotiate this kind of resources are required. This paper presents an approach to deal with these issues, by using a multi-agent simulator able to model demand side players and simulate their strategic behavior. The paper includes an illustrative case study that considers an incident situation. The distribution company is able to reduce load curtailment due to load flexibility contracts previously established with demand side players.
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The smart grid concept is rapidly evolving in the direction of practical implementations able to bring smart grid advantages into practice. Evolution in legacy equipment and infrastructures is not sufficient to accomplish the smart grid goals as it does not consider the needs of the players operating in a complex environment which is dynamic and competitive in nature. Artificial intelligence based applications can provide solutions to these problems, supporting decentralized intelligence and decision-making. A case study illustrates the importance of Virtual Power Players (VPP) and multi-player negotiation in the context of smart grids. This case study is based on real data and aims at optimizing energy resource management, considering generation, storage and demand response.
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Demand response can play a very relevant role in future power systems in which distributed generation can help to assure service continuity in some fault situations. This paper deals with the demand response concept and discusses its use in the context of competitive electricity markets and intensive use of distributed generation. The paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes using a realistic network simulation based on PSCAD. Demand response opportunities are used in an optimized way considering flexible contracts between consumers and suppliers. A case study evidences the advantages of using flexible contracts and optimizing the available generation when there is a lack of supply.
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Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica
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The discussion and analysis of the diverse outreach activities in this article provide guidance and suggestions for academic librarians who are interested in outreach and community engagement of any scale and nature. Cases are draw from a wide spectrum and are particularly strong in the setting of large academic libraries, special collections and programming for multicultural populations. The aim of this study is to present the results of research carried out regarding the needs, demand and consumption of European Union information by users in European Documentation Centres (EDC). A quantitative methodology was chosen based on a questionnaire with 24 items. This questionnaire was distributed within the EDC of Salamanca, Spain, and the EDC of Porto, Portugal, during specific time intervals between 2010 and 2011. We examined the level of EU information that EDC users possess, and identified the factors that facilitate or hinder access to EU information, the topics most demanded, and the types of documents consulted. Analysis was made of the use that the consumer of European information makes of databases and their behaviour during the consultation. Although the sample used was not very significant owing to its small size, it is a faithful reflection of the scarce visits made to EDCs. This study can be of use to managers of EDCs, providing them with better knowledge of the information needs and demands of their users. Ultimately this should lead to improvements in the services offered. The study lies within a frame of research scarcely addressed in specialized scholarly literature: European Union information.
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Competitive electricity markets have arisen as a result of power-sector restructuration and power-system deregulation. The players participating in competitive electricity markets must define strategies and make decisions using all the available information and business opportunities.
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This study aimed to carry out experimental work to obtain, for Newtonian and non-Newtonian fluids, heat transfer coefficients, at constant wall temperature as boundary condition, in fully developed laminar flow inside a helical coil. The Newtonian fluids studied were aqueous solutions of glycerol, 25%, 36%, 43%, 59% and 78% (w/w) and the non-Newtonian fluids aqueous solutions of carboxymethylcellulose (CMC), a polymer, with concentrations 0.1%, 0.2%, 0.3%, 0.4% and 0.6% (w/w) and aqueous solutions of xanthan gum (XG), another polymer, with concentrations 0.1% and 0.2% (w/w). According to the rheological study performed, the polymer solutions had shear thinning behavior and different values of elasticity. The helical coil used has internal diameter, curvature ratio, length and pitch, respectively: 0.004575 m, 0.0263, 5.0 m and 11.34 mm. The Nusselt numbers for the CMC solutions are, on average, slightly higher than those for Newtonian fluids, for identical Prandtl and generalized Dean numbers. As outcome, the viscous component of the shear thinning polymer tends to potentiate the mixing effect of the Dean cells. The Nusselt numbers of the XG solutions are significant lower than those of the Newtonian solutions, for identical Prandtl and generalized Dean numbers. Therefore, the elastic component of the polymer tends to diminish the mixing effect of the Dean cells. A global correlation, for Nusselt number as a function of Péclet, generalized Dean and Weissenberg numbers for all Newtonian and non-Newtonian solutions studied, is presented.
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OBJECTIVES: Estimate the frequency of online searches on the topic of smoking and analyze the quality of online resources available to smokers interested in giving up smoking. METHODS: Search engines were used to revise searches and online resources related to stopping smoking in Brazil in 2010. The number of searches was determined using analytical tools available on Google Ads; the number and type of sites were determined by replicating the search patterns of internet users. The sites were classified according to content (advertising, library of articles and other). The quality of the sites was analyzed using the Smoking Treatment Scale- Content (STS-C) and the Smoking Treatment Scale - Rating (STS-R). RESULTS: A total of 642,446 searches was carried out. Around a third of the 113 sites encountered were of the 'library' type, i.e. they only contained articles, followed by sites containing clinical advertising (18.6) and professional education (10.6). Thirteen of the sites offered advice on quitting directed at smokers. The majority of the sites did not contain evidence-based information, were not interactive and did not have the possibility of communicating with users after the first contact. Other limitations we came across were a lack of financial disclosure as well as no guarantee of privacy concerning information obtained and no distinction made between editorial content and advertisements. CONCLUSIONS: There is a disparity between the high demand for online support in giving up smoking and the scarcity of quality online resources for smokers. It is necessary to develop interactive, customized online resources based on evidence and random clinical testing in order to improve the support available to Brazilian smokers.
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This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.
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OBJECTIVE To evaluate the cross-cultural validity of the Demand-Control Questionnaire, comparing the original Swedish questionnaire with the Brazilian version. METHODS We compared data from 362 Swedish and 399 Brazilian health workers. Confirmatory and exploratory factor analyses were performed to test structural validity, using the robust weighted least squares mean and variance-adjusted (WLSMV) estimator. Construct validity, using hypotheses testing, was evaluated through the inspection of the mean score distribution of the scale dimensions according to sociodemographic and social support at work variables. RESULTS The confirmatory and exploratory factor analyses supported the instrument in three dimensions (for Swedish and Brazilians): psychological demands, skill discretion and decision authority. The best-fit model was achieved by including an error correlation between work fast and work intensely (psychological demands) and removing the item repetitive work (skill discretion). Hypotheses testing showed that workers with university degree had higher scores on skill discretion and decision authority and those with high levels of Social Support at Work had lower scores on psychological demands and higher scores on decision authority. CONCLUSIONS The results supported the equivalent dimensional structures across the two culturally different work contexts. Skill discretion and decision authority formed two distinct dimensions and the item repetitive work should be removed.